Papers by Stephen D. Richardson

2 papers
Neuron-Level Language Tag Injection Improves Zero-Shot Translation Performance (2025.acl-srw)

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Challenge: Language tagging is a method that trains models on specific language directions . injection is based on a language token embedded in the input layer .
Approach: They propose a method whereby source and target inputs are prefixed with a unique language token and inject it into the input of every linear layer.
Outcome: The proposed method improves translation performance with up to 2+ BLEU score point gain for certain language directions in a multilingual dataset.
The Effects of Pretraining in Video-Guided Machine Translation (2024.lrec-main)

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Challenge: Existing approaches to improve VMT models integrate text and video modalities.
Approach: They propose an approach that improves the performance of VMT models by using a new dataset which contains transcribed audio descriptions of movies.
Outcome: The proposed model improves on the MAD (Movie Audio Descriptions) dataset.

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